One deficiency of the MA criterion and its generalizations is that it is difficult to incorporate certain design principles such as effect sparsity and effect hierarchy. In the nonregular factorial setting, Bingham and Chipman (2007) use a Bayesian approach for incorporating prior information in optimal design selection. Having pre-specified which models are most plausible, their methodology allows the user to select designs (possibly nonregular) that discriminate between competing models. A natural extension of this research would be to adapt such techniques to the split-plot setting. This topic is presently under consideration.